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Test-Time Data Augmentation
Tutorial on how to properly implement test-time image data augmentation in a production environment with limited computational resources.
data-augmentation keras production tensorflow
From Research to Production with Deep Semi-Supervised Learning
Semi-Supervised Learning (SSL) has blossomed in the deep learning research community — we share lessons learned over 15 months of taking SSL into ...
semi-supervised-learning deep-learning production machine-learning
Omega|ml - building and deploying ML models the easy way
Deploying ML is hard. It should not be. omega|ml makes it a breeze.
mlops production code article
What I Learned From Looking at 200 Machine Learning Tools
To better understand the landscape of available tools for machine learning production, I decided to look up every AI/ML tool I could find.
production machine-learning mlops survey
Feature Stores for ML
List of production ML groups and their open-source feature store architectures.
feature-store production industry tutorial
Using GitHub Actions for MLOps & Data Science
A collection of resources on how to facilitate Machine Learning Ops with GitHub.
github ml-ops production github-actions
Machine Learning Deployment: Shadow Mode
“How do I test my new model in production?” One answer, and a method I often employ when initially deploying models, is shadow mode.
deployment production shadow-mode article
DeepR — Training TensorFlow Models for Production
DeepR is a Python library to build complex pipelines as easily as possible on top of Tensorflow.
production tensorflow pipelines mlflow
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